Why is transforming data important?

Data Transformation

The complexity of data in today’s marketing world is increasing day by day, making it difficult for organizations to drive actionable insights from the big data silos. Analyzing valuable information requires structured and accessible data for achieving the best results. In such a scenario, the concept of data transformation comes into the picture. With the help of the big data transformation tools, users can alter the structure and format of the raw data as required. In this article, we will learn about the proven useful data transformation technologies, but first, let take a look at the brief explanation of data transformation.

What is Data Transformation?

Data transformation is a process in which the raw data is converted into a single and easy-to-read format so that the same can be further used for analysis. It’s all about turning your data into something that makes sense. With such a transformation, you can drive valuable and actionable information from the data that helps you make the right decisions at the right time. 

Data transformation also goes by the name ETL (Extract, Transform, Load), the complete process of aggregating data from multiple sources, transforming it into a particular format, and loading it into the desired location. The data loaded into your preferred data warehouse powers the analysis and reporting processes. 

Data transformation is a two-stage process that includes the following:

Stage 1

Stage 2

In the second stage of data transformation, the data experts extract the data from the original source. The sources can vary based on their structure, database, and streaming services, like log files from web portals. The experts will also perform transformation and convert the data extracted from multiple platforms like social media, sales, etc. into a lucid format. The transformed data is then transferred into the target location, mainly a database or a data warehouse that can efficiently handle large volumes of data.

Benefits of Transforming Data

How To Transform Data?

Data Transformation can add rockets to your organizational efficiency of performing analytic and business processes and enable better decision making. The first phase of data transformation must include conversion and flattening of hierarchical data. This will help you structure data to improve compatibility with analytics systems. You can further implement transformations according to the layers of processing required. 

Here’s how data transformation is done:

BI tools can also be used to automate the process of filtering and aggregation to make the data more efficient before reporting tools to access it.

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